1. Field of the Invention
The present invention relates to an image processing method and an image processor for extracting continuous line segments from a variable density image, and more particularly to an image processing method and an image processor for extracting a linearly connected area from a variable density image, considering the growth direction of the line segments.
2. Description of the Related Art
As current demands for advancements in personal authentication technology increases, many personal authentication technologies using image data acquired by capturing the image of a body (test subject) have been proposed. For example, an image of a portion which can identify an individual, such as fingerprints, eye retina, face and blood vessels, is captured and a characteristic part is extracted from the captured image for personal authentication. The portion suitable for such personal authentication is a portion formed of relatively continuous line segments.
A captured image, on the other hand, has relatively low contrast and includes noise depending on the ambient environment and the image capturing status, so innovation is required for this technology to extract these continuous line segments accurately. For this technology to extract continuous line segments from an image, edge enhancement processing and morphology processing for tracking line segments are effective.
Conventionally it has been proposed that the captured image is binarized, then line segments are extracted using a morphology function and Gaussian Laplacian filter (see Japanese Patent Application Laid-Open No. 2004-329825 (FIG. 3)). However it is difficult to detect line segments accurately by applying morphology technology to an image after binarizing since grayscale data acquired from the captured image is not used.
Also as a method of performing morphology processing on grayscale data, it has been proposed to perform open processing and top hat processing, which is one morphology processing on grayscale data for extracting line segments, such as an image of vessels from the retina image of a human eye (“Segmentation of Vessel-Like Pattern using Mathematical Morphology and Curvature Evaluation” (F. Zana, J. C. Klein, IEEE Trans. Image Processing, Vol. 10, pp. 1010 to 1019, July 2001).